Comprehensive AI agent customization Tools for Every Need

Get access to AI agent customization solutions that address multiple requirements. One-stop resources for streamlined workflows.

AI agent customization

  • Jotform AI Agents automate customer service tasks, providing real-time assistance and enhancing user interactions.
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    What is Jotform AI Agents?
    Jotform AI Agents are innovative software tools that automate customer service and support tasks. They provide real-time assistance, answer user queries, and guide customers through various processes. By leveraging conversational AI technology, these agents improve efficiency, reduce the workload on human agents, and enhance the overall user experience. Jotform AI Agents can be customized to match your brand's voice and are designed to seamlessly integrate with different platforms, offering dynamic and interactive customer service solutions.
  • MInD provides memory management for LLM-based agents to record, retrieve, and summarize contextual information across sessions.
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    What is MInD?
    MInD is a Python-based memory framework designed to augment LLM-driven AI agents with robust memory capabilities. It enables agents to capture user inputs and system events as episodic logs, condense those logs into semantic summaries, and retrieve contextually relevant memories on demand. With configurable retention policies, similarity search, and automated summarization, MInD maintains a persistent knowledge base that agents consult during inference. This ensures they recall prior interactions accurately, adapt responses based on history, and deliver personalized, coherent dialogues across multiple sessions.
  • A lightweight JavaScript framework for building AI agents with memory management and tool integration.
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    What is Tongui Agent?
    Tongui Agent provides a modular architecture for creating AI agents that can maintain conversation state, leverage external tools, and coordinate multiple sub-agents. Developers configure LLM backends, define custom actions, and attach memory modules to store context. The framework includes an SDK, CLI, and middleware hooks for observability, making it easy to integrate into web or Node.js applications. Supported LLMs include OpenAI, Azure OpenAI, and open-source models.
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